A resource-awareness information extraction architecture on mobile grid environment

With the advances in mobile grid technology, it is possible to store ever greater amounts of information in the mobile data grid environment. The issues of information retrieval and knowledge discovery from wireless or mobile grids are becoming increasingly important. In this paper, we use mobile agent technology to propose the RAKER, a resource-aware information extraction architecture on the mobile grid. The RAKER can dynamically determine processing and policies for information extraction, employing our proposed resource estimation model to achieve high levels of performance and availability. With it, mobile users can extract information or knowledge stored on mobile grids in an efficient, effective and transparent way without worrying about the most important issue in mobile computing, which is energy consumption. We show the implementation with an example to demonstrate the use of RAKER. In addition, we display its performance by measuring latency and energy consumption and simulating the availability of the system.

[1]  Gang Wang,et al.  A Knowledge Grid Architecture Based on Mobile Agent , 2006, SKG.

[2]  Sam Malek,et al.  A Framework for Estimating the Impact of a Distributed Software System's Architectural Style on its Energy Consumption , 2008, Seventh Working IEEE/IFIP Conference on Software Architecture (WICSA 2008).

[3]  Kam-Wing Ng,et al.  Performance Evaluation of Mobile Grid Services , 2008, KES-AMSTA.

[4]  Mario Cannataro,et al.  Distributed data mining on the grid , 2002, Future Gener. Comput. Syst..

[5]  Jason J. Jung Contextualized mobile recommendation service based on interactive social network discovered from mobile users , 2009, Expert Syst. Appl..

[6]  Samuel Pierre,et al.  Mobile agents and their use for information retrieval: a brief overview and an elaborate case study , 2002, IEEE Netw..

[7]  Feng Pan,et al.  Exploring the energy-time tradeoff in high-performance computing , 2005, 19th IEEE International Parallel and Distributed Processing Symposium.

[8]  Chang-Qin Huang,et al.  Power-Aware Hierarchical Scheduling with Respect to Resource Intermittence in Wireless Grids , 2006, 2006 International Conference on Machine Learning and Cybernetics.

[9]  Nalini Venkatasubramanian,et al.  An energy-efficient middleware for supporting multimedia services in mobile grid environments , 2005, International Conference on Information Technology: Coding and Computing (ITCC'05) - Volume II.

[10]  Kam-Wing Ng,et al.  MGS: An API for Developing Mobile Grid Services , 2006, OTM Conferences.

[11]  I-Tung Yang,et al.  Impact of budget uncertainty on project time-cost tradeoff , 2005, IEEE Transactions on Engineering Management.

[12]  Giuseppe De Pietro,et al.  MiPeG: A middleware infrastructure for pervasive grids , 2008, Future Gener. Comput. Syst..

[13]  Mario Cannataro,et al.  Distributed data mining on grids: services, tools, and applications , 2004, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[14]  Xianfeng Li,et al.  Estimating the Worst-Case Energy Consumption of Embedded Software , 2006, 12th IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS'06).

[15]  Wenyu Qu,et al.  Efficient Information Retrieval by Dispatching Mobile Agents in Parallel , 2008, 2008 International Conference on Multimedia and Ubiquitous Engineering (mue 2008).

[16]  Lee W. McKnight,et al.  Guest Editors' Introduction: Wireless Grids--Distributed Resource Sharing by Mobile, Nomadic, and Fixed Devices , 2004, IEEE Internet Comput..

[17]  Shonali Krishnaswamy,et al.  A hybrid model for improving response time in distributed data mining , 2004, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[18]  Ching-Hsien Hsu,et al.  A Peer-to-Peer Resource Sharing System with Data Grid Technology for Mobile Devices , 2007, 2007 International Conference on Multimedia and Ubiquitous Engineering (MUE'07).

[19]  Jun Hu,et al.  Distributed data mining on Agent Grid: Issues, platform and development toolkit , 2007, Future Gener. Comput. Syst..

[20]  Thomas Phan,et al.  Challenge: integrating mobile wireless devices into the computational grid , 2002, MobiCom '02.

[21]  William E. Allcock,et al.  The Globus Striped GridFTP Framework and Server , 2005, ACM/IEEE SC 2005 Conference (SC'05).

[22]  Yue-Shan Chang,et al.  RARS: a Resource-Aware Replica Selection and co-allocation scheme for mobile grid , 2010, Int. J. Ad Hoc Ubiquitous Comput..

[23]  Anish Muttreja,et al.  Hybrid Simulation for Energy Estimation of Embedded Software , 2007, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems.

[24]  Chan Huah Yong,et al.  On Fairness, Optimizing Replica Selection in Data Grids , 2009, IEEE Transactions on Parallel and Distributed Systems.

[25]  Yue-Shan Chang,et al.  Adaptive Knowledge Retrieving on Mobile Grid , 2008, 2008 Eighth International Conference on Intelligent Systems Design and Applications.

[26]  Jason J. Jung Social grid platform for collaborative online learning on blogosphere: A case study of eLearning@BlogGrid , 2009, Expert Syst. Appl..

[27]  Giovanni De Micheli,et al.  OS-Based Sensor Node Platform and Energy Estimation Model for Health-Care Wireless Sensor Networks , 2008, 2008 Design, Automation and Test in Europe.

[28]  George V. Tsoulos,et al.  An agent-based framework for integrating mobility into grid services , 2008 .

[29]  Vlado Stankovski,et al.  Grid-enabling data mining applications with DataMiningGrid: An architectural perspective , 2008, Future Gener. Comput. Syst..

[30]  Dimitrios Skoutas,et al.  Efficient task replication and management for adaptive fault tolerance in Mobile Grid environments , 2007, Future Gener. Comput. Syst..

[31]  Theodora Varvarigou,et al.  MOBILE GRID COMPUTING: CHANGES AND CHALLENGES OF RESOURCE MANAGEMENT IN A ΜOBILE GRID ENVIRONMENT , 2003 .